Project Summary/Abstract TheEbolaepidemicthatravagedWestAfricafrom2013to2016isbyfarthelargestoutbreakeverrecorded. Weak healthcare infrastructure, community resistance, and a slow uncoordinated response, allowed the epidemic tospinoutofcontrol.Theregion,however,isnostrangertodealingwithviralhemorrhagicfevers. LassafeveriscausedbyinfectionwithLassavirusandishyper-endemicinWestAfrica.Lassafeverissimilar toEbolainthatinfectionwithLassaviruscanleadtoaseverehemorrhagicfever.InfectionswithbothLassa virus and Ebola virus can lead to deaths in more than 70% of hospitalized patients. It is estimated that tens of thousands of people die from Lassa fever each year. These numbers are likely underestimates, as the healthcare infrastructure in the a?ected countries is extremely weak, surveillance almost non-existent, and most patients never present in thehospital.Despitethehighcasefatalityratesof hospitalized Ebola and Lassa fever patients, however, some people appear to be able to quickly ?ght the viruses,whereasothersdiequicklyfrominfection.Yet,whatdistinguishesfatalfromnon-fataldiseaseandthe development of symptomatic versus asymptomatic infection, remain largely unknown and severely understudied.ThegoaloftheConsortiumforViralSystemsBiologyistouncoverthevirusandhumanfactors that determine how infected individuals are able to better ?ght the viruses. We will achieve this goal by investigating the following three broad aims: Aim 1. De?ne virus and host factors responsible for survival and non-survival in Ebola and Lassa fever patients. Aim 2. Identify factors that play roles in the development of severe long-term symptoms in survivors. Aim 3. De?ne factors that determine whether human individuals develop symptomatic or asymptomatic disease. We will accomplish these aims by applying several ?omics? technologies, physiological measurements,and high-throughput experimental approaches to unique patient and survivor cohortsofLassafeverandEbola. We will develop novel predictive statistical models for identifying critical disease correlates and analyze large-scale data sets to pinpoint causal host-pathogen interactions. By elucidation the molecular networks thatplaycriticalrolesinpatientoutcomes,thisresearchwillallowustoidentifynewtargetsformedicinesand vaccinesandinformpersonalizedtreatmentstrategies.Ourstudywillalsoprovidenovelresearchframeworks and computational algorithms applicable to a wide range of other human pathogens.